ABSTRACT

Global
gene expression patterns of Bacillus subtilis in response to
subinhibitory concentrations of protein synthesis inhibitors
(chloramphenicol, erythromycin, and gentamicin) were studied by DNA
microarray analysis. B. subtilis cultures were treated with
subinhibitory concentrations of protein synthesis inhibitors for 5, 15,
30, and 60 min, and transcriptional patterns were measured throughout
the time course. Three major classes of genes were affected by the
protein synthesis inhibitors: genes encoding transport/binding
proteins, genes involved in protein synthesis, and genes involved in
the metabolism of carbohydrates and related molecules. Similar
expression patterns for a few classes of genes were observed due to
treatment with chloramphenicol (0.4× MIC) or erythromycin
(0.5× MIC), whereas expression patterns of gentamicin-treated
cells were distinct. Expression of genes involved in metabolism of
amino acids was altered by treatment with chloramphenicol and
erythromycin but not by treatment with gentamicin. Heat shock genes
were induced by gentamicin but repressed by chloramphenicol. Other
genes induced by the protein synthesis inhibitors included the
yheIH operon encoding ABC transporter-like proteins, with
similarity to multidrug efflux proteins, and the ysbAB operon
encoding homologs of LrgAB that function to inhibit cell wall cleavage
(murein hydrolase activity) and convey penicillin tolerance in
Staphylococcus
aureus.

Over the past decade, bacterial resistance to antibiotics has risen
dramatically and “superbugs” resistant to most or all
available agents have appeared in hospitals. Thus, there is an urgent
need to discover and develop novel classes of antibiotics
(11). The availability of
the complete genome sequence of many pathogenic microbes provides
information on potential drug targets. Approaches such as
bioinformatics or whole-genome transcriptional analysis are now used to
search for drug targets (reviewed in references
34 and
37). Genome-wide
expression profiling generated by DNA microarrays can be used to
observe differential gene expression in response to environmental
stimuli or genetic alterations. Studies of transcriptional profiles of
bacteria treated with an inhibitor can provide valuable information
useful for both pathway characterization and for determination of the
mechanism of the inhibitor
(14,
42). In addition,
differential expression of essential genes or previously
uncharacterized genes caused by an inhibitor may identify the
corresponding gene products as potential drug targets
(22). Recently, several
studies have been performed to study transcriptional or translational
profiles of microorganisms subjected to one class of antibiotics
(2,
8,
14,
23,
28,
40), or several classes
of antibiotics (3,
6,
12,
16-18,
33), to generate
databases that can be used to distinguish modes of actions of
antimicrobial agents.

In the present study, we used DNA
microarray analysis to determine the global gene expression pattern of
Bacillus subtilis in response to subinhibitory concentrations
of protein synthesis inhibitors: chloramphenicol, erythromycin, and
gentamicin. Chloramphenicol is known to block peptidyl transferase
activity by hindering the binding of tRNA to the A site
(24,
32). Erythromycin, a
macrolide, is believed to block the tunnel that channels the nascent
peptides away from the peptidyl transferase center, thereby preventing
movement and release of the nascent peptide
(32). Gentamicin is an
aminoglycoside that binds to a conserved sequence of rRNA that is near
the site of codon-anticodon recognition in the aminoacyl-tRNA site (A
site) of the 30S ribosomal subunit. This interaction in turn interferes
with proofreading steps that ensure translational fidelity
(9,
44). Both chloramphenicol
and erythromycin target the 50S ribosomal subunit and inhibit
translation elongation, whereas gentamicin targets the 30S ribosomal
subunit and affects translational accuracy. We would like to generate
transcriptional profiles of cells treated with protein synthesis
inhibitors or other classes of antibiotics to create a library of
signature responses for the determination of modes of action of new
antimicrobial compounds. Microbial transcriptional or translational
profiles after treatment with antibiotics or drugs have been determined
recently, and statistical or mathematical tools can be applied to
predict modes of actions of different compounds
(3,
6,
17). Genes highly induced
or repressed by protein synthesis inhibitors can potentially be used as
signature genes to identify new drugs that inhibit translation. B.
subtilis is an ideal microorganism for microarray analysis because
its genome has been sequenced
(20). Gene expression
responses to higher concentrations of inhibitors have been shown to
cause a broader effect on cellular processes, thereby giving much more
complex response patterns
(14,
34). We applied
subinhibitory concentrations (concentrations that cause little growth
inhibition) of protein synthesis inhibitors with the goal of observing
antibiotic-specific primary expression profiles and that
growth-inhibition-related secondary responses would be
underrepresented. Multiple concentrations of inhibitors were applied so
that dose-specific effects could be examined. Furthermore, a time
course of 5 to 60 min was applied so that the kinetics of the
transcription response over time could be studied. Several common major
functional classes of genes were affected by the protein synthesis
inhibitors used. These classes include transport/binding proteins and
lipoproteins, metabolism of carbohydrates and related molecules, and
protein synthesis.

Bacterial
growth conditions.Standard
broth microdilution assays were performed to determine the MICs of
B. subtilis against chloramphenicol, erythromycin, or
gentamicin (27).
Overnight cultures of B. subtilis 1A757 were diluted 1:100 in
Mueller-Hinton medium and incubated at 37°C with shaking at 200
rpm. When cultures reached an optical density at 600 nm
(OD600) of 0.2, chloramphenicol at 0.05× (0.2μ
g/ml), 0.25× (1 μg/ml), or 0.4× (1.6μ
g/ml) MIC; erythromycin at 0.1× (0.0125μ
g/ml), 0.25× (0.03125 μg/ml), or 0.5×
(0.0625 μg/ml) MIC; or gentamicin at 0.1× (0.0125μ
g/ml), 0.25× (0.03125 μg/ml), or 0.4×
(0.05 μg/ml) MIC was added to the cultures. Untreated cultures
were used as controls. Samples were collected at 5, 15, 30, and 60 min
after treatment for subsequent RNA isolation. The samples were
processed immediately by centrifugation, and pellets were stored at−
80°C. Growth and viability were monitored for at least
2.5 h posttreatment by measuring both the OD600
and CFU at several time points.

RNA
isolation, probe preparation, and hybridization for DNA
microarrays.RNA samples
were extracted independently from two experiments, and isolation was
performed with the FastRNA Blue Kit (Qbiogene, Carlsbad, CA) according
to the manufacturer's instructions. Fluorescent probes were
prepared by reverse transcription (RT) of 25 μg of total RNA to
incorporate aminoallyl-dUTP into first strand cDNA. The amino-cDNA was
then labeled by direct coupling to either Cy3 (cDNA from untreated
sample) or Cy5 (cDNA from antibiotic-treated sample) monofunctional
reactive dyes (Amersham Biosciences, Piscataway, NJ). DNA microarrays
consisting of PCR-amplified B. subtilis 168 open reading
frames (ORFs) or ORF-specific oligonucleotides (60-mers) at a 10μ
M concentration in 3× SSC (1× SSC is 0.15 M
NaCl plus 0.015 M sodium citrate; Compugen, Jamesburg, NJ) were also
used as described previously
(4,
5). All labeled cDNA
probes were hybridized to oligonucleotide slides with the exception of
one chloramphenicol-treated experiment that was hybridized to slides
spotted with PCR products. Hybridizations were performed as previously
described (4,
5). The corresponding cDNA
samples for treatment and control were mixed and hybridized to the
microarray slides in replicates of a total of six genomes. The slide
images were scanned and edited by using an Axon 4000B scanner (Axon
Instruments, Union City, CA).

DNA
microarray data analysis and clustering analysis.The fluorescent signal ratios
(Cy5/Cy3) were subjected to Lowess normalization with background
correction in the GeneSpring software (Silicon Genetics, Redwood City,
CA). The normalized data was then analyzed by a statistical technique,
significance analysis for microarrays (SAM), to identify significantly
up- or downregulated genes with the exclusion of invariant genes
(39). SAM assigns a score
to each gene on the basis of its change in expression relative to the
standard deviation of repeated measurements for that gene. A“
q value” assigned to each gene corresponds to
the lowest false discovery rate at which the gene is called
significant. The “one class response” was used, and the
number of falsely significant genes was set to be less than one in SAM.
The differentially expressed genes identified by SAM were further
filtered to identify genes whose ratios of expression in treated versus
untreated control were more than 1.5 or less than 0.67, indicating at
least a 1.5-fold change of expression. Clustering analysis was
performed by using best k-means provided in GeneSpring (reviewed in
reference 36). We used
the “best k-means” script in GeneSpring to determine
the optimal number of the clusters for each analysis. The data used for
clustering analysis was from treatment with each of the three
concentrations of antibiotics over the time series (5, 15, 30, and 60
min). Genes used for clustering had to meet the following requirements:
(i) genes had to be determined by SAM to be significantly variant; (ii)
gene expression levels has to be above or below the cutoff range
(1.5-fold); and (iii) the amount of up- or downregulation had to be
consistent in two independent experiments and at least one
condition. Expression ratios used for clustering analysis
were average fluorescence intensity ratios from two independent
experiments, each consisting of data from six microarray replicates (a
total of 12 datum points per
gene).

The RT-PCRs contained
serial dilutions of RNA templates, 500 nM concentrations of each pair
of primers, 1× SYBR Green PCR Master Mix (Applied Biosystems,
Foster City, CA), and 0.24 U of Moloney murine leukemia virus reverse
transcriptase (Invitrogen, Carlsbad, CA)/μl.Reverse transcription was performed at 50°C for 30 min,
followed by inactivation of reverse transcriptase and activation of
AmpliTaq DNA polymerase at 95°C for 15 min. For each
dilution triplicate reactions were prepared. Forty thermocycles were
performed as follows: 94°C for 15 s, 55°C for
30 s, and 72°C for 30 s. The RNA samples
were also subjected to RT-PCR amplification with the yecA or
yvaN primers. The amount of PCR product at each cycle was
recorded by measuring fluorescence generated by binding of the SYBR dye
to double-stranded DNA. The amplification plot generated with untreated
(time zero) samples was used as the reference curve to standardize
amplification results generated from the untreated and
antibiotic-treated samples. The results were then normalized to the
data generated from the yecA or yvaN amplification
for chloramphenicol and erythromycin or gentamicin-treated samples,
respectively.

RESULTS

Growth
of B. subtilis in the presence of subinhibitory concentrations
of chloramphenicol, erythromycin, and gentamicin.The MICs of B. subtilis
against chloramphenicol, erythromycin, and gentamicin were determined
to be 4, 0.125, and 0.125 μg/ml, respectively. B.
subtilis cultures were treated with 0.05×, 0.25×,
or 0.4× MIC of chloramphenicol; 0.1×, 0.25×, or
0.5× MIC of erythromycin; or 0.1×, 0.25×, or
0.4× MIC of gentamicin. The concentrations were selected based
on their subinhibitory phenotypes after antibiotic treatment measured
by OD600 and CFU (data not shown). When chloramphenicol was
applied to B. subtilis cultures, all treatments caused growth
inhibitory effect after 60 min. When erythromycin was applied,
0.1× and 0.25× MIC treatments caused inhibitory effect
after 60 min, whereas the 0.5× MIC-treated cultures showed
growth inhibition as early as 15 min. Finally, when gentamicin was
applied, 0.4× MIC treatment led to inhibition as early as 15
min, and 0.1× MIC- and 0.25× MIC-treated cultures
displayed growth inhibition after 60 min. In summary, most conditions
studied did not cause strong growth inhibition of B.
subtilis.

Microarray experimental
design and data analysis.B. subtilis cultures were
treated with subinhibitory concentrations of chloramphenicol,
erythromycin, or gentamicin. Untreated cultures were used as control.
Total RNA was extracted from each culture 5, 15, 30, and 60 min after
treatment. Subinhibitory concentrations of inhibitors were used to
avoid secondary responses caused by high concentrations of antibiotics.
Multiple concentrations of antibiotics were tested to study
dose-dependent effects. Furthermore, a time course of 5 to 60 min was
applied so that the kinetics of the transcription response to time
could be determined. RNA samples were used to prepare cDNA for
subsequent Cy dye labeling and hybridization to microarrays. The
control (no treatment) samples were labeled with Cy3, and treated
samples were labeled with Cy5. The corresponding samples for each time
point and treatment were mixed and hybridized to multiple microarray
slides equivalent to at least six genomes.

The fluorescence
intensity values, calculated by dividing the Cy5 signal by the Cy3
signal, were quantified, normalized, and assessed by SAM software to
identify genes whose expression was significantly altered by treatment
with antibiotics. The false discovery rate at which the gene is called
significant was less than 0.5% for genes accepted to be
significant with a few exceptions. The genes determined by SAM to be
significant were then filtered to identify genes whose Cy5/Cy3 ratios
were more than 1.5 or less than 0.67 (indicating more than a 1.5-fold
change of expression).

Overview of
transcriptional profiles of chloramphenicol-, erythromycin-,
or gentamicin-treated B. subtilis cells.Treatment of B. subtilis with
chloramphenicol, erythromycin, or gentamicin revealed a total of 856,
1,233, or 462 genes, respectively, up- or downregulated by at least
1.5-fold in two independent experiments and in at least one condition.
Approximately 20% of the differentially expressed genes encode
proteins with similarity to those with unknown functions in other
organisms, whereas ca. 10% encode proteins with no homologs.
Analysis of genes with known functions revealed that all three
antibiotics primarily affected the transcription of genes from the
following three categories: transport/binding protein genes, genes
involved in protein synthesis, and genes involved in metabolism of
carbohydrates and related molecules (Fig.
1). In addition, for all three antibiotics the frequencies of occurrence
of genes in other functional categories whose expression was affected
were similar. We also found subtle differences in abundance
of genes in the major categories for chloramphenicol and erythromycin
versus gentamicin. For example, there was a larger percentage of genes
involved in transport/binding proteins and metabolism of amino acids
for chloramphenicol- or erythromycin-treated cultures than for
gentamicin-treated cultures. In contrast, larger percentages of genes
involved in protein synthesis and metabolism of carbohydrates were
affected by gentamicin than by chloramphenicol or
erythromycin.

Distribution
of functions of genes whose expression levels were affected by
treatment with antibiotics. The top 11 functional categories affected
by the protein synthesis inhibitors are illustrated. The
category of each gene was assigned by SubtiList
(http://genolist.pasteur.fr/SubtiList/),
a website created by B. subtilis Genome Sequencing Project.
The percent occurrence frequency is the percentage of the total number
of genes in each functional category affected by each protein synthesis
inhibitor.

Since chloramphenicol, erythromycin, and gentamicin
primarily affected transcription of genes from the same three major
functional categories, we studied expression patterns of genes from
each of these functional groups. Average expression levels of category
genes grouped by k-means clustering at each concentration were studied.
Expression ratios of representative genes in each major functional
category affected by the highest concentration of antibiotics are
listed in Table
1. The representative genes shown in Table
1 were among those
considered significant by SAM at a given time and dose in both
experiments and were consistently regulated (either up- or
downregulated) in both experiments. Expression patterns were similar
for a few gene classes when cells were treated with the highest
concentration tested for chloramphenicol (0.4× MIC) or
erythromycin (0.5× MIC). When treated with the 0.4× or
0.5× MIC of chloramphenicol or erythromycin, respectively, many
genes encoding transport/binding proteins were upregulated at 15 min.
In addition, genes involved in protein synthesis showed a similar
expression profile peaking at 15 min, followed by a gradual decrease
after 30 min. Genes involved in the metabolism of carbohydrates were
upregulated at 30 min by treatment with chloramphenicol and
downregulated at 60 min by treatment with erythromycin. Gene expression
patterns observed in gentamicin-treated cultures differed from those
due to chloramphenicol or erythromycin treatment. When treated with
gentamicin, many genes encoding transport/binding proteins or genes
involved in metabolism of carbohydrates were downregulated at 15 min,
whereas some protein synthesis genes were upregulated at 5 and 30 min
and downregulated at 15 and 60 min. The similarity of expression
patterns affected by highest tested concentrations of chloramphenicol
and erythromycin may reflect the similar modes of action of the two
antibiotics, since both antibiotics target the 50S ribosomal
subunit.

Transcriptional response to
different concentrations of antibiotics.Erythromycin and gentamicin treatment
usually generated expression profiles that were similar regardless of
dose. However, expression patterns due to chloramphenicol treatment
usually showed a dose-dependent difference (data not shown).
Occasionally, more than one trend of expression patterns was observed,
such as expression of genes encoding transport proteins or genes
involved in protein synthesis upon treatment with chloramphenicol, and
expression patterns of protein synthesis genes due to treatment with
erythromycin. Expression patterns of four genes involved in protein
synthesis due to treatment with three different concentrations of
gentamicin are shown in Fig.
2, top panel. Similar expression patterns (upregulated at 5 and 30 min and
downregulated at 15 and 60 min) were observed regardless of
concentrations in both experiments, a finding consistent with the
patterns shown in Table 1.
Moreover, dose-dependent effects were observed for rplJ,
rplO, and rpsN especially at the 5- and 15-min time
points. Upon treatment with erythromycin, many genes consistently
upregulated at 15 min in all three treated concentrations were
identified. Representative genes (cotD, ykuC,
yqeD, and yxjA) that displayed dose dependence at 15
min are depicted in Fig.
2, bottom panel.
Similarly, they were repressed or invariant by 60 min, except for
yxjA, which remained upregulated throughout treatment (data
not shown).

Average
gene expression ratios upon treatment with gentamicin or erythromycin.
(Top panel) Average expression ratios of rplJ, rplO,
rpsK, and rpsN genes upon treatment with
0.1×, 0.25×, or 0.4× MIC of gentamicin for 5,
15, 30, or 60 min. (Bottom panel) Dose-dependent expression ratios of
cotD (spore coat protein), ykuC (similar to
macrolide-efflux protein), yqeD (unknown), and yxjA
(similar to pyrimidine nucleoside transport) genes upon treatment with
0.1×, 0.25×, or 0.5× MIC of erythromycin for 15
min. Values of more than one indicate induction, and values of less
than one indicate repression. The error bars depict the standard
deviation from 12 datum points in two independent
experiments.

Validation of gene
expression by real-time RT-PCR analysis.The real-time RT-PCR analysis was
chosen as an independent method to validate microarray results since it
measures product accumulation during the linear phase of the PCR and is
an accurate and reproducible approach to gene quantification
(30,
31). We quantified
transcripts of genes involved in protein synthesis (rplF,
ribosomal protein L6), transport proteins (rbsB, ribose ABC
transporters), heat shock (groES, class I heat shock protein;
clpP, class III heat shock protein), and cold shock
(cspB and cspD, cold shock proteins) due to treatment
with chloramphenicol, erythromycin, or gentamicin in at least one
condition. Relative quantities of each gene's transcription level
in untreated and treated samples were determined and normalized by
using the internal control genes, which were invariant on treatment
with chloramphenicol and erythromycin (yecA, encoding a
unknown protein that is similar to amino acid permease) or gentamicin
(yvaN gene, encoding a unknown protein that is similar to
immunity repressor protein). Finally, the ratios from treated/untreated
samples were determined. The results are shown in Table
2. All genes were validated except for groES under one condition.
Consistent with previous observations, differences in the magnitude of
expression ratios between microarray analysis and real-time RT-PCR were
observed
(30).

Transcription
responses specific to erythromycin, chloramphenicol, and/or
gentamicin.We examined
additional functional category genes that showed consistent regulation
patterns with treatment by chloramphenicol, erythromycin, or
gentamicin. Expression of genes involved in metabolism of amino acids
was consistently affected by erythromycin and chloramphenicol,
sometimes in a dose-dependent manner when treated with erythromycin.
Genes involved in the metabolism of amino acids, including
glnA, glyA, goxB, pepT, and
rocA, were downregulated at 60 min at higher concentrations of
chloramphenicol, whereas glyA, hisD, rocA,
rocD, and rocG were downregulated at 60 min by
treatment with 0.5× erythromycin (Table
1).

Expression of
genes involved in purine and pyrimidine synthesis was altered upon
treatment with either chloramphenicol or erythromycin. Genes involved
in purine and pyrimidine synthesis were upregulated at 15 min upon
treatment with chloramphenicol, whereas expression was downregulated at
60 min with erythromycin treatment at all concentrations. Expression
levels of representative genes involved in purine and pyrimidine
biosynthesis are listed in Table
1. We found that many
genes involved in purine/pyrimidine biosynthesis were regulated
similarly to protein synthesis genes when treated with 0.4× MIC
of chloramphenicol (Table
1). The coregulation of
genes involved in purine/pyrimidine biosynthesis and those in protein
synthesis was also observed in B. subtilis cultures treated
with 0.5× MIC of cephalothin (M. Maranta and D. S.
Yaver, unpublished data).

Heat shock genes were upregulated by
gentamicin, especially at later time points, in all three
concentrations. Notably, a dose-dependent regulatory effect was
observed for the expression of clpP at 60 min (Tables
1 and
2). Furthermore, an
upregulation in the expression of heat shock genes was also observed
due to treatment with streptomycin (another aminoglycoside, data not
shown). In contrast, expression of heat shock genes was repressed by
treatment with chloramphenicol (Tables
1 and
2), with maximum
repression observed after 15 min due to treatment with 0.25× or
0.4× MIC. Heat shock genes appeared to be sparingly affected by
treatment with erythromycin (data not shown). Finally, the expression
of ykuC, which is similar to macrolide efflux protein, was
induced by erythromycin at 15 min in a dose-dependent manner (Fig.
2, bottom
panel).

Genes most highly induced with
chloramphenicol, erythromycin, or gentamicin treatment.We analyzed genes that were highly
induced due to antibiotic treatment at any concentration or time point.
Genes highly induced by erythromycin included dctP,
dppB, rpsF, ycnB, yonS,
ysbA, ysbB, ytiP, and yvsH. These
genes were usually upregulated at 15 or 60 min, with dctP most
highly induced. Genes highly induced by chloramphenicol included
gapB, mcpB, rbsB, yheH,
yheI, yrzI, ysbA, and ysbB.
Expression of these genes was upregulated after 15 min with treatment
at various concentrations. Interestingly, yheI and
yheH form an operon and encode ABC transporter-like proteins
with similarity to multidrug efflux proteins
(29). Genes highly
induced by gentamicin include clpP, ysbA,
ysbB, and yxiE. These genes were highly expressed at
60 min posttreatment. Expression of ysbA and ysbB
were consistently highly induced by all three antibiotics tested and
are located in an operon. They are currently annotated in the SubtiList
website
(http://genolist.pasteur.fr/SubtiList/)
as unknown proteins or similar to proteins of unknown functions. We
performed a homology search by using the blastp program and determined
that ysbAB gene products are homologous to the lrgAB
gene products in Staphylococcus aureus
(15). The amino acid
sequences of ysbA- and ysbB-encoding proteins are 44
and 57% identical to the LrgA and LrgB proteins, respectively,
from S. aureus. The LrgAB proteins inhibit extracellular
murein hydrolase activity (the enzymes that cleave structural
components of the bacterial cell wall) as well as convey penicillin
tolerance in S. aureus
(15).

Genes with
similar expression patterns with yheH or ysbAB were
further analyzed by best k-means clustering analysis. The genes that
clustered with yheH or ysbAB, and their relative
expression levels are listed in Table
3. The yheH gene was highly induced after 15 min with
chloramphenicol treatment at all concentrations tested. The
ysbA and ysbB gene were induced after 30 min of
treatment with any concentration of chloramphenicol or erythromycin.
Finally, gentamicin treatment resulted in an induction of ysbA
and ysbB at 60 min. The yheI gene was expressed
similarly with yheH, which is in the same operon, at all
chloramphenicol concentrations tested. The dctP gene, encoding
a C4-dicarboxylate transport protein, displayed an
expression profile similar to yheH with 0.4× MIC
chloramphenicol treatment. Interestingly, the dctP gene also
exhibited expression patterns similar to those for ysbA and
ysbB when treated with higher concentrations (0.25×
and 0.4×/0.5×) of chloramphenicol, erythromycin, or
gentamicin. The ysbA and ysbB genes were also
regulated similarly to yheH upon treatment with 0.4×
MIC of chloramphenicol. In all erythromycin and gentamicin experiments,
ysbA and ysbB had expression profiles similar to
those of yolF and yxiE, respectively. The function of
yolF is unknown, whereas yxiE is known to be induced
by phosphate starvation
(1). Homology searches
with yolF and yxiE failed to reveal any similarity to
known proteins (data not
shown).

Expression
ratios of genes that were highly expressed or involved in transcription
regulatory functions in response to various concentrations of
chloramphenicol, erythromycin, or gentamicin

Transcriptional regulators
affected by protein synthesis inhibitors.We investigated transcriptional
regulators whose expression was altered by treatment with protein
synthesis inhibitors. Expression levels of representative genes are
listed in Table 3.
Transcriptional regulators that were affected by all three protein
synthesis inhibitors include PyrR. When pyrimidines are abundant, the
PyrR protein binds to the conserved sequence in the pyr operon
mRNA and disrupts the antiterminator, permitting terminator hairpin
formation and promoting transcription termination
(35,
38). Transcription of
pyrR was induced at 15 min in all concentrations of
erythromycin treatment. Similarly, pyrR gene expression peaked
at 15 min and remained induced at 60 min after the addition of
chloramphenicol. Gentamicin treatment resulted in increased expression
of pyrR at 5 and 15 min at all concentrations. Genes in the
pyrR regulon, the
pyrRPBC(AA)(AB)KDFE operon, were
induced at 15 min, but expression decreased after 15 min of treatment
with all of the protein synthesis inhibitors tested (data not
shown).

Expression of the lmrAB operon was induced at 15
min by at least twofold due to treatment with gentamicin or
erythromycin at all concentrations. The lmrA gene encodes a
negative regulator that autogenously represses the transcription of the
operon, and the lmrB gene product is a drug efflux pump
(19,
25,
43). The expression of
the lmrAB operon was reduced after 15 min in erythromycin or
gentamicin-treated cultures, probably due to repression by LmrA.
Expression of lmrA and lmrB appeared to be unaffected
by chloramphenicol
treatment.

DISCUSSION

We used microarray
analysis to study transcriptional profiles of B. subtilis
cultures treated with subinhibitory concentrations of chloramphenicol,
erythromycin, and gentamicin. In order to study the kinetics of the
transcriptional response induced by protein synthesis inhibitors, a
time course of 5 to 60 min and multiple concentrations of antibiotic
were applied. We found that the largest number of genes affected by the
three protein synthesis inhibitors included genes encoding
transport/binding proteins, genes involved in metabolism of
carbohydrates, and genes involved in protein synthesis. In addition,
expression patterns were similar in two functional classes when cells
were treated with the highest concentration of chloramphenicol and
erythromycin. This similarity in expression patterns may reflect the
fact that both antibiotics target the 50S ribosomal
subunit.

Intriguingly, the same three functional classes of genes
that were affected by the protein synthesis inhibitors were also
affected by antibiotics inhibiting cell wall, RNA, or DNA synthesis (M.
Maranta, C. Amolo, H. Ge, and D. S. Yaver, unpublished data).
This presents the possibility that altered transcriptional expression
of genes in these categories is a universal response to general stress
caused by treatment with antibiotics. However, expression profiles were
distinct among the antibiotics with different mechanisms of action,
indicating that specific transcriptional responses resulted from
different antibiotic treatments.

The stringent response is a
process that enhances survival during starvation stress and coincides
with the rapid accumulation of guanosine
3′-5′-bispyrophosphate (ppGpp). The hallmark of the
stringent response is the negative regulation of components of the
translational apparatus including rRNAs, tRNAs, ribosomal proteins, and
translation factors (10,
13). Several studies have
shown that while transcriptional and translational inhibitors cause
decreased synthesis of the stringent factor ppGpp in Escherichia
coli, some aminoglycosides such as neomycin, streptomycin, or
spectinomycin had little effect on the level of ppGpp
(21,
26). A similar effect was
observed in Haemophilus influenzae when transcriptional and
proteomic analyses were performed in the presence of transcriptional
and translational inhibitors
(12). The authors of that
study found that ribosomal protein synthesis rates were increased by
treatment with most protein synthesis inhibitors. However,
aminoglycoside such as streptomycin had little effect. These
researchers further demonstrated that the transcriptional and
translational responses to translational inhibitors were coordinately
mediated by the synthesis of ppGpp. Proteomic studies in B.
subtilis also showed that inhibitors of translation elongation
(such as tetracycline, chloramphenicol, and erythromycin) induced the
rate of synthesis of the stringently controlled ribosomal proteins and
elongation factors, whereas aminoglycosides (such as gentamicin,
kanamycin, and streptomycin), which interfere with ribosomal
translation accuracy, did not
(3). Consistently, we
found that expression of ribosomal protein and elongation factor genes
was induced by chloramphenicol and erythromycin, whereas genes coding
for elongation factors were not affected by gentamicin. However, our
results showed that gentamicin can trigger transcriptional induction of
genes encoding ribosomal proteins even 5 min posttreatment (Table
1). A real-time RT-PCR
experiment validated that one of the ribosomal protein genes,
rplF, was indeed induced at the early time point (Table
2). Many ribosomal protein
genes showed dynamic gene regulation after treatment with gentamicin
(i.e., up at 5 min, down at 15 min, up at 30 min, and then down at 60
min) (Tables 1 and
2). This discrepancy could
be due to our use of subinhibitory concentrations of antibiotic (versus
the higher dosages used in the other studies) or to other differences
in experimental conditions.

Other functional categories affected
by both chloramphenicol and erythromycin included genes involved in
metabolism of amino acids (Table
1). The similar expression
profiles between genes encoding ribosomal proteins and genes involved
in purine/pyrimidine biosynthesis due to treatment with chloramphenicol
could be due to coregulation (i.e., repression of the stringent
response). Genes involved in purine/pyrimidine biosynthesis were shown
to be repressed under conditions that provoke stringent response, but
regulation was relA independent
(13).

Previous
studies in E. coli showed that the H group antibiotics (such
as aminoglycosides) induce heat shock response, whereas the C group
antibiotics (such as erythromycin and chloramphenicol) induce cold
shock and repress heat shock genes
(7,
41). A recent study also
confirmed that the heat shock response was triggered by treatment with
kanamycin (33). A
proteomic study in B. subtilis confirmed that aminoglycosides
induced expression of heat shock proteins, but the authors did not
observe induction of cold shock proteins by chloramphenicol or
erythromycin (3). In our
study, a few cold shock genes were induced by treatment with
chloramphenicol or erythromycin in some of the experiments, but
induction was not consistent for most cold shock genes (Table
2 and data not shown). A
whole-genome transcriptional analysis of a gram-positive bacterium
Streptococcus pneumoniae also showed that, although
streptomycin induced heat shock genes, erythromycin and chloramphenicol
did not alter heat shock gene expression
(28). Our data are
consistent with the Bacillus and Streptococcus
studies in that gentamicin, as well as streptomycin, induced heat shock
genes. The delayed induction (at 60 min) of the heat shock genes on
treatment with gentamicin is consistent with studies by VanBogelen and
Neidhardt in E. coli
(41). These researchers
found that, whereas temperature shifts resulted in an immediate
induction of heat shock proteins, the addition of antibiotics such as
aminoglycosides resulted in a much delayed heat shock response. In
contrast to the studies described above, we show here that the
expression of heat shock genes was repressed by chloramphenicol. These
microarray results were validated by real-time RT-PCR analysis (Table
2). Again, the discrepancy
could be due to experimental design and conditions. We could be
observing a more primary effect, since altered expression of heat shock
genes by treatment with chloramphenicol was observed after 15 min when
the growth inhibitory effect was still minimal.

The effects of
sublethal concentrations of translation inhibitors (chloramphenicol,
erythromycin, tetracycline, and puromycin) on global transcription
patterns of S. pneumoniae R6 was previously studied
(28). These researchers
found that genes from the major biological categories that were
affected by translation inhibitors included genes involved in
translation, transport and carrier proteins, and in amino acid
biosynthesis. As mentioned above, we found similar classes
of genes being regulated in chloramphenicol- and erythromycin-treated
B. subtilis cultures.

We examined genes that were highly
induced due to treatment with chloramphenicol, erythromycin, or
gentamicin. Of particular interest were the yheIH and
ysbAB operons. The expression of yheIH was highly
induced by chloramphenicol after 15 min, whereas the expression of
ysbAB was highly induced by all three antibiotics tested. The
yheI and yheH genes were previously shown to encode
ABC transporter-like proteins which were classified in subfamily 6 of
B. subtilis ATP-binding proteins
(29). Proteins in
subfamily 6 are similar to multidrug resistance proteins of eukaryotes
and prokaryotes. The YheI/YheH proteins might constitute four
heterodimer ABC transporters. The ysbAB gene products are
homologous to the lrgAB gene products in S. aureus.
The LrgAB proteins confer negative control on extracellular murein
hydrolase activity (the enzymes that cleave structural components of
the bacterial cell wall), as well as decreased sensitivity to
penicillin-induced killing in S. aureus
(15). The lrgAB
genes form an operon and encode for antiholin-like membrane proteins
that were hypothesized to inhibit the formation of murein hydrolase
transport channels (holin) in the bacterial membrane. Since
ysbAB homologs function to inhibit cell wall cleavage (the
murein hydrolase activity) and convey penicillin tolerance in S.
aureus, it is slightly surprising to observe that ysbAB
were induced by protein synthesis inhibitors. Our observation suggests
that ysbA and ysbB may be involved in tolerance to
protein synthesis inhibitors as well. Furthermore, the ysbAB
genes were coregulated with yheH under 0.4× MIC
chloramphenicol treatment, implying that they could share a
similar function with the putative multidrug resistance protein.
Sensitivity toward penicillin and protein synthesis inhibitors in
B. subtilis strains overexpressing ysbAB is currently
being studied.

We also investigated transcriptional regulators
that were affected by chloramphenicol, erythromycin, and gentamicin.
The pyrR gene, the transcription attenuation factor of the
pyrR operon involved in pyrimidine biosynthesis, was induced
after 15 min by all three protein synthesis inhibitors. As expected,
the increased expression of the PyrR transcription attenuator leads to
repression of the genes in the pyrR regulon after 15 min of
antibiotic treatment. Expression of the lmrA gene, encoding a
negative regulator of transcription of the lmrAB operon, was
readily induced at 15 min by treatment with erythromycin or gentamicin.
The lmrB gene, encoding a multidrug-resistant efflux protein,
of the lmrAB operon was also induced at 15 min by erythromycin
or gentamicin (25).
Expression of the lmrAB operon was decreased after 15 min,
possibly due to repression by the negative transcription regulator
LmrA. Induction of lmrB may indicate a self-defense mechanism
induced by treatment with erythromycin and gentamicin.

In
summary, we determined the expression profiles of chloramphenicol-,
erythromycin-, and gentamicin-treated B. subtilis cultures and
showed that transcription of several major functional classes of genes
was affected. Genes that were specifically affected by treatment with
protein synthesis inhibitors could potentially be used as signature
genes, along with signature genes from cultures treated with other
antibiotics for determination of modes of action of new
drugs.

ACKNOWLEDGMENTS

We thank Randy Berka and
Alan Sloma for critical reading of the
manuscript.